The CHORUS gap analysis on user-centered methodology for design and evaluation of multi-media information access systems

CHORUS is a Coordination Action, a specific type of project funded by the European commission under its research programmes, intended to bring together research projects with common goals, in the field of search technologies for digital audio-visual content, one of the strategic objectives of the current research frame program. CHORUS coordinates a number of research projects in the general area of audio-visual and multi-media information access and management. The most important single contribution of the CHORUS work plan will be to provide a survey of the field and a roadmap with a gap analysis for the realisation of viable audio-visual search engines by European partners. This is done by several means. CHORUS organises Think-Tanks with industrial participation, focussed workshops to treat specific questions, and more general conferences for academic discussions. CHORUS is now in its final phase, and is currently preparing its final report together with a final conference to mark its publication

Desirable properties for XML update mechanisms

The adoption of XML as the default data interchange format and the standardisation of the XPath and XQuery languages has resulted in significant research in the development and implementation of XML databases capable of processing queries efficiently. The ever-increasing deployment of XML in industry and the real-world requirement to support efficient updates to XML documents has more recently prompted research in dynamic XML labelling schemes. In this paper, we provide an overview of the recent research in dynamic XML labelling schemes. Our motivation is to define a set of properties that represent a more holistic dynamic labelling scheme and present our findings through an evaluation matrix for most of the existing schemes that provide update functionality

Vibration-based adaptive novelty detection method for monitoring faults in a kinematic chain

Postprint (published version

Generalized Completed Local Binary Patterns for Time-Efficient Steel Surface Defect Classification

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.Efficient defect classification is one of the most important preconditions to achieve online quality inspection for hot-rolled strip steels. It is extremely challenging owing to various defect appearances, large intraclass variation, ambiguous interclass distance, and unstable gray values. In this paper, a generalized completed local binary patterns (GCLBP) framework is proposed. Two variants of improved completed local binary patterns (ICLBP) and improved completed noise-invariant local-structure patterns (ICNLP) under the GCLBP framework are developed for steel surface defect classification. Different from conventional local binary patterns variants, descriptive information hidden in nonuniform patterns is innovatively excavated for the better defect representation. This paper focuses on the following aspects. First, a lightweight searching algorithm is established for exploiting the dominant nonuniform patterns (DNUPs). Second, a hybrid pattern code mapping mechanism is proposed to encode all the uniform patterns and DNUPs. Third, feature extraction is carried out under the GCLBP framework. Finally, histogram matching is efficiently accomplished by simple nearest-neighbor classifier. The classification accuracy and time efficiency are verified on a widely recognized texture database (Outex) and a real-world steel surface defect database [Northeastern University (NEU)]. The experimental results promise that the proposed method can be widely applied in online automatic optical inspection instruments for hot-rolled strip steel.Peer reviewe

Modelling Discourse-related terminology in OntoLingAnnot’s ontologies

Recently, computational linguists have shown great interest in discourse annotation in an attempt to capture the internal relations in texts. With this aim, we have formalized the linguistic knowledge associated to discourse into different linguistic ontologies. In this paper, we present the most prominent discourse-related terms and concepts included in the ontologies of the OntoLingAnnot annotation model. They show the different units, values, attributes, relations, layers and strata included in the discourse annotation level of the OntoLingAnnot model, within which these ontologies are included, used and evaluated